OP0276 PREFERENCES FOR TREATMENTS TO PREVENT RHEUMATOID ARTHRITIS: DISCRETE CHOICE SURVEY OF RHEUMATOID ARTHRITIS PATIENTS’ FIRST-DEGREE RELATIVES IN THE UNITED KINGDOM AND GERMANY.
Authors: G. Simons, J. Veldwijk, R. Disantostefano, M. Englbrecht, C. Radawski, L. Valor, J. Humphreys, I. N. Bruce, K. Raza, M. Falahee
Journal: Annals of the Rheumatic Diseases (2022)

Background There is a growing research focus on the development of interventions to reduce risk of rheumatoid arthritis (RA) in at-risk individuals.(1) A recent survey of the general population asked to assume a 60% risk of RA established that hypothetical preventive treatments were acceptable to most participants.(2) However the preferences of individuals who actually have an elevated risk of RA, such as first-degree relatives (FDRs) of RA patients, are not well understood. Objectives To quantify FDRs’ preferences for preventive treatments for RA. Methods Adult FDRs in the UK and Germany were invited to take part in a web-based survey via patients with clinician-confirmed RA either during a rheumatology clinic visit or by mail. In addition, FDRs taking part in a UK-based prospective cohort (PREVeNT-RA) were invited via email. Participants received information about RA followed by questions to check comprehension, and an introduction to the survey including warm-up questions. They were asked to imagine they were experiencing arthralgia and had positive autoantibody tests indicating a 60% chance of developing RA in the next two years. Using a discrete choice experiment, participants were offered a series of 15 choices between no treatment and two unlabeled hypothetical treatments to reduce risk of RA. Treatments were defined by six attributes with varying levels, describing benefits, risks, and frequency/route of administration (Table 1). Attribute selection and presentation was informed by qualitative research, ranking surveys, systematic literature review, and expert opinion. Survey layout was informed by patient research partners and qualitative pre-testing. A two-class latent class analysis was used to estimate preferences and calculate relative importance of treatment attributes and predicted uptake. A panel mixed logit model was used to obtain maximum acceptable risk estimates. Table 1. Treatment attributes and levels Attribute Levels Chance of developing RA reduced from 60% to 10%; 20%; 30%; 40% How the treatment is taken A shallow injection under the skin A drip into the vein One or two tablets How often the medication has to be taken Daily Weekly Monthly Every 6 months Chance of mild side effects 2%; 5%; 10% Chance of a serious infection due to treatment 0%; 1%; 5% Chance of a serious side effect that is potentially irreversible 1 in 100,000 people 20 in 100,000 people 100 in 100,000 people Results 356 FDRs (252 female, 289 in the UK) responded. While treatment effectiveness was the most important attribute in both classes (Figure 1), the importance of other attributes differed between classes, with method and frequency of treatment administration being more important in class 2 and risk of mild side effects only impacting treatment choice in class 1. Perceived risk of developing RA predicted class assignment; those with higher perceived risk were more likely to belong to class 1. On average, the predicted uptake of treatment profiles estimating prevention candidates: abatacept; atorvastatin; hydroxychloroquine; tolerogenic cell-based therapy; and no treatment would be 50%, 15%, 9%, 18% and 0%, respectively. Finally, the maximum acceptable risk participants were willing to accept were 81%, 25% and 3% point increases in risk of mild side effects, serious infection, and serious side effects, respectively, for medicines that would reduce their risk of developing RA in the upcoming two years from 60% to 20%. Conclusion Effective preventive treatments for RA were acceptable to FDRs asked to assume a 60% chance of developing RA. Mode and frequency of treatment administration had a greater impact on treatment choices for participants with a lower perceived risk of RA. These findings are informative for target product profile development, endpoint selection, benefit-risk assessment, regulatory approval, and development of informational resources for those at risk of RA. References [1]Mankia et al. Ann Rheum Dis. 2021;80(10):1286-98. [2]Simons et al. Ann Rheum Dis. 2021;80:96-7. Acknowledgements On behalf of the PREFER project. PREFER received funding from the IMI 2 Joint Undertaking (grant No. 115966), which receives support from the EU’s Horizon 2020 research and innovation program and European Federation of Pharmaceutical Industries and Associations (EFPIA). This abstract and its contents reflect the view of the presenter and not the view of PREFER, IMI, the European Union or EFPIA. K. Raza is supported by the NIHR Birmingham Biomedical Research Centre. Disclosure of Interests Gwenda Simons: None declared, Jorien Veldwijk: None declared, Rachael DiSantostefano Shareholder of: Johnson &amp; Johnson, Employee of: Janssen Research and Development, Matthias Englbrecht Speakers bureau: Abbvie, Chugai, Eli Lilly, Novartis, Roche, Sanofi, Munidpharma, Paid instructor for: Abbvie, Chugai, Roche, Consultant of: Abbvie, Novartis, Roche, Sanofi, Grant/research support from: Roche, Chugai, Christine Radawski Shareholder of: Eli Lilly &amp; Company, Employee of: Eli Lilly &amp; Company, Larissa Valor: None declared, Jenny Humphreys: None declared, Ian N. Bruce: None declared, Karim Raza Consultant of: Abbvie, Sanofi, Grant/research support from: Bristol Myers Squibb, Marie Falahee: None declared